Posts Tagged ‘Engineering’

Scanning radiation flux with moving sensors in Energy2D

July 13th, 2014 by Charles Xie
Figure 1: Moving sensors facing a rectangular radiator.
The heat flux sensor in Energy2D can be used to measure radiative heat flux, as well as conductive and convective heat fluxes. Radiative heat flux depends on not only the temperature of the object the sensor measures but also the angle at which it faces the object. The latter is known as the view factor.

In radiative heat transfer, a view factor between two surfaces A and B is the proportion of the radiation which leaves surface A that strikes surface B. If the two surfaces face each other directly, the view factor is greater than the case in which they do not. If the two surfaces are closer, the view factor is greater.

Figure 2: Rotating sensors inside and outside a ring radiator.
To conveniently visualize the effect of a view factor, Energy2D allows you to attach a heat flux sensor to a moving or rotating particle, with a settable linear or angular velocity. In this way, we can set up sensors to automatically "scan" the field of radiation heat flux like a radar.

Figure 1 shows a moving sensor and a rotating sensor, as well as the data they record. A third sensor is also placed to the right of an object that is being heated by the radiator. This object has an emissivity of one so it also radiates. Its radiation flux is recorded by the third sensor whose data shows a slowly increasing heat flux as the object slowly warms up.

As an interesting test case, Figure 2 shows two rotating sensors, one placed precisely at the center of a ring radiator and the other outside. The almost steady line recorded by the first sensor suggests that the view factor at the center does not change, which makes sense. The small sawtooth shape is due to the limitation of discretization in our numerical simulation.

Spring is here, let there be trees!

March 28th, 2014 by Charles Xie
Trees in Energy3D.
Trees around a house not only add natural beauty but also increase energy efficiency. Deciduous trees to the south of a house let sunlight shine into the house through south-facing windows in the winter while blocking sunlight in the summer, thus providing a simple but effective solution that attains both passive heating and passive cooling using the trees' shedding cycles. Trees to the west and east of a house can also create significant shading to help keep the house cool in the summer. All together, a well-planed landscape can reduce the temperature of a house in a hot day by up to 20°C.

The tree to the south side shades the house in the summer.
With the latest version of Energy3D, students can add trees in designs. As shown in the second image in this blog post, the Solar Irradiation Simulator in Energy3D can visualize how trees shade the house and provide passive cooling in the summer.

The Solar Irradiation Simulator also provides numeric results to help students make design decisions. The calculated data show that the tree to the south of the house is able to reduce the sunlight shined through the window on the first floor that is closest to it by almost 90%. Students can do this easily by adding and removing the tree, re-run the simulation, and then compare the numbers. They will be able to add trees of different heights and types (deciduous or evergreen). There will be a lot of design variables that students can choose and test.

A design challenge is to combine windows, solar panels, and trees to reduce the yearly cost of a building to nearly zero or even negative (meaning that the owner of the house actually makes money by giving unused energy produced by the solar panels to the utility company). This is no longer just a possibility -- it has been a reality, even in a northern state like Massachusetts!

Modeling Physical Behavior with an Atomic Engine

May 13th, 2013 by Sara Remsen

Our Next-Generation Molecular Workbench (MW) software usually models molecular dynamics—from states of matter and phase changes to diffusion and gas laws. Recently, we adapted the Molecular Dynamics 2D engine to model macroscale physics mechanics as well, including pendulums and springs.

In order to scale up the models from microscopic to macroscopic, we employ specific unit-scaling conventions. The Next-Generation Molecular Workbench (MW) engine simulates molecular behavior by treating atoms as particles that obey Newton’s laws. For example, the bond between two atoms is treated as a spring that obeys Hooke’s law, and electrostatic interactions between charged ions follow Coulomb’s Law.

Dipole-dipole interactions simulated using Coulomb’s Law.

At the microscale, the Next-Generation MW engine calculates the forces between molecules or atoms using atomic mass units (amu), nanometers (10−9 meters) and femtoseconds (10-15 seconds), and depicts their motion. To simulate macroscopic particles that follow the same laws, we can imagine them as microscopic particles with masses in amu, distance in nanometers, and timescales measured in femtoseconds. Once the Next-Generation MW engine calculates the movement of these atomic-scale particles, we simply multiply the length, mass and time units by the correct scaling factors. This motion satisfies the same physical laws as the atomic motion but is now measured in meters, kilograms and seconds.

In the pendulum simulation below, the Next-Generation MW engine models the behavior of a pendulum by treating it as two atoms connected by a very stiff bond with a very long equilibrium length. The topmost atom is restrained to become a “pivot” while the bottom atom “swings” because of the stiff bond. Once the engine has calculated the force using the atomic-scale units, it converts the mass, velocity and acceleration to the appropriate units for large, physical objects like the pendulum.

Large-scale physical behavior simulated with a molecular dynamics engine.

In order to appropriately model the physical behavior of a pendulum or a spring, we use specific scaling constants. Independent scaling constants for mass, distance and time enable us to convert nanometers to meters, atomic mass units to kilograms and femtoseconds to model seconds. Using the same scaling constants, we can derive other physical conversions, such as elementary charge unit to Coulomb. In order to make one model second pass for every real second, we adjusted the amount of model time between each page refresh. We also chose to simulate a gravitation field—a feature usually absent in molecular dynamics simulators—because it is relevant to macroscopic phenomena.

From microscale to macroscale, the Next-Generation Molecular Workbench engine is a powerful modeling tool that we can use to simulate a wide variety of biological, chemical, and physical phenomena.  Find more simulations at mw.concord.org/nextgen/interactives.

Engineers use Energy2D to simulate rocket mass heaters

April 24th, 2013 by Charles Xie
Link to simulation
A rocket mass heater is an innovative and highly efficient space heating system, which is popular among natural building DIYers since its invention in 1970s. A number of engineers who are interested in rocket stove design have used our Energy2D software to visualize the thermal physics involved.
Link to simulation

Martin Karl Waldenburg from Germany has designed a series of simplified rocket stove simulations. With his permission, we have published his simulations on our Energy2D website. This blog post provides links to three of his simulations. Another one was created by Pinhead of the Rocket Stove Forum (who also gave us permission to publish his simulation).

Link to simulation
Link to simulation
Since Energy2D hasn't supported chemical reactions yet, in all these simulations, burning is simulated using a heater with a fan to approximate the driving pressure due to combustion.

We will continue to work on Energy2D's computational engine and improve its graphical user interface. Currently, we are plowing through the math needed to model thermal radiation, chemical reactions, and phase changes. Once these features are added, we hope more people will find it useful, educational, and entertaining.

NSTA Reports features the Engineering Energy Efficiency Project

January 2nd, 2013 by Charles Xie
Link to NSTA news
NSTA Reports is the National Science Teachers Association’s newspaper published nine times a year as a free member service. In January, our Engineering Energy Efficiency Project was one of the three projects featured in a report about "meaningfully integrating science and engineering."

The Engineering Energy Efficiency Project is funded by the National Science Foundation through a research grant.

Detecting students’ "brain waves" during engineering design using a CAD tool

December 12th, 2012 by Charles Xie
Design a city block with Energy3D.
We were in a school these two weeks doing a project that aims to understand how students learn engineering design. This has been a difficult research topic as engineering design is an extremely complicated cognitive process that involves the application of science and mathematics -- another two sets of complicated subjects themselves.


Two types of problems are commonly encountered in the classroom. The first type is related to using a "cookbook" approach that confines students to step-by-step procedures to complete a "design" project. I added double quotes because this kind of project often leads to identical or similar products from students, violating the first principle of design that mandates alternatives and varieties. However, if we make the design project completely open-ended, we will run into the second type of problem: The arbitrariness and caprice in student designs often make it difficult for teachers and researchers to assess student thinking and learning reliably. As much as we want students to be creative and open-minded, we also want to ensure that they learn what is intended and we must provide an objective way to evaluate their learning outcomes.


To tackle these issues, we are taking a computer science-based approach. Computer-aided design (CAD) tools offer an opportunity for us to move the entire process of engineering design to the computer (this is what CAD tools are designed for in the first place for industry folks). What we need to do in our research is to add a few more things to support data mining.

A sample design of the city block.
This blog post reports a timeline tool that we have developed to measure student activity levels while engaged in using a CAD tool (our Energy3D CAD software in this case) to solve a design challenge. This timeline tool is basically a logger that records the number of the learner's design actions at a given frequency (say, 2-4 times a minute) during a design session. These design actions are defined to be the "atomic" actions stored in the Undo Manager of the CAD tool we are using. The timeline approximately describes the user's frequency of construction actions with the CAD tool. As the human-computer interaction is ultimately driven by the brain, this kind of timeline data could be regarded as a reflection of the user's "brain wave."

There are four things that characterize such a timeline graph:

A sample timeline graph.
  • The height of a spike measures the action intensity at that moment, i.e., how many actions the user has taken since the last recording;
  • The density of spikes measures the continuity and persistence of actions over a time period;
  • A gap indicates an off-task time window: A short idling window may be an effect of instruction or discussion;
  • The trend of height and density may be related to loss of interest or improvement of proficiency in the CAD tool: If the intensity (the combination of height and density of spikes) drops consistently over time, the student's interest may be fading away; if the intensity increases consistently over time, the student might be improving on using the design tool to explore design options.
Timeline graphs from six students.
Of course, this kind of timeline data is not perfect. It certainly has many limitations in measuring learning. We are still in the process of analyzing these timeline data and juxtaposing them with other artifacts we have gathered from the students to provide a more comprehensive picture of design learning. But the timeline analysis represents a rudimentary step towards a more rigorous methodology for performance assessment of engineering design.

The above six "brain wave" graphs were collected from six students in a 90-minute class period. Hopefully, these data will lead to a way to identify novice designers' behaviors and patterns when they are solving a design challenge.

Energy2D to reach thousands of schools

August 17th, 2012 by Charles Xie
Thermoregulation
Project Lead The Way (PLTW) is the leading provider of rigorous and innovative Science, Technology, Engineering, and Mathematics (STEM) education curricular programs used in middle and high schools across the US. The PLTW Pathway To Engineering (PTE) program includes a foundational course called the Principles of Engineering (POE) designed for 10-11th grade students. PLTW curriculum currently reaches 4,780 schools.

According to Bennett Brown, Associate Director of Curriculum and Instruction of PLTW, our Energy2D software will be adopted in the POE curriculum to support a variety of core engineering concepts including power, energy, heat transfer, controls, and environmental factors.
Solar heating cycles

Since the release of the first alpha version in 2011, Energy2D has already been used by thousands of users worldwide, but the collaboration with PLTW will be a big step forward for Energy2D to reach more students. The timing of this collaboration is particularly important to engineering tools such as Energy2D, as--for the first time--engineering has been officially written into the US K-12 Science Education Standards. Once the Standards roll out, thousands of teachers will be looking for leading-edge tools that can help them teach engineering. This will be a great opportunity for Energy2D.

Why is Energy2D so special that people want to use it? Our website provides many self-explanatory examples. But there is one hidden gem I want to emphasize here: Its computational engine is based on good algorithms I devised specially for this simulator. Its heat solver can be so accurate that a simulation can maintain the total energy of an isolated system at a level as accurate as 99.99% for as long as it runs, regardless of the complexity of the structures in the system! The fact that the sum of energy from all the 10,000 grid cells remains a constant after billions of individual calculation steps reflects the holy grail of science and engineering. If anything, engineering is about accuracy. A good engineering tool should be able to give students a good engineering habit of mind and accuracy should be a paramount part of it.

Energy2D V1.0 released!

August 3rd, 2012 by Charles Xie
The first stable version of Energy2D, an open-source and free heat transfer simulation tool made possible by funding from the National Science Foundation, is now available for download. The program can be installed as a desktop app, which can be used to create high-quality simulations that can be deployed on the Internet as applets. It comes with about 40 templates to help you get started to design your own simulations. The Energy2D website provides plenty of examples that show how you can integrate your simulations on your websites. The examples cover a wide range of topics in heat transfer, fluid dynamics, and thermal engineering. Thermal engineering is a major feature added recently and will be expanded in the future. The example to the right, "How solar cycles affect the duty cycle of a thermostat," showcases this new feature.

When you click the "Java Webstart Installer" on the website, the software will be automatically downloaded and installed on your desktop. The website's Download page has detailed information for how to publish your Energy2D simulations or integrate them with your web stuff.

If you have used the Energy2D app before, you will need to remove the previous installation in order to enjoy the convenience of full OS integration that this version offers. For Windows users, go to "Control Panel > Java." For Mac users, go to the Java Preference. In either case, you can find the previous installation in "Temporary Internet Files."

If you have just used the online applets on our website but haven't downloaded the app, there is nothing you need to remove. Although it is perfectly fine to use the online applets as they are, we think you should try the app--It will give you the full ability to create, design, and test.

"Semi-digital" fabrication technologies

April 25th, 2012 by Charles Xie
A street made by using Energy3D.

Emerging digital fabrication technologies such as 3D printing could trigger a new wave of industrial revolution according to New Scientist. While 3D printers are becoming more affordable and they are growing more powerful, versatile, and speedy, they will likely not be immediately available in the classroom.


Fabrication in schools is fundamentally important to engineering education. The lack of appropriate educational technology that supports students to transform ideas into products could impede student learning and creativity. To meet schools' immediate needs and fill the gap between now and future, we have been developing a flagship app called Energy3D that provides a "semi-digital" solution for fabrication.

The current version of Energy3D focuses on designing, constructing, and testing model buildings. The program supports students to conceive and design a building on the computer. It then converts a computer design into a sketch on paper that can be printed out using a conventional printer. Students can then cut out the pieces from the sketch and then assemble them into buildings as designed. The reason we call this technology "semi-digital" fabrication is because, while the computer helps generate the sketch, students still need to cut and assemble manually.

This has a catch, however, as it assumes the pieces are all as thin as a piece of paper. But for education, it is perfectly fine because it reduces the design and manufacturing complexity for young students, allowing them to address a tractable number of important questions related to math, architecture, engineering, and science.

We are going to the 2012 USA Science and Engineering Festival to be held in Washington DC in April 28-29 to demonstrate this technology. If you happen to be there and are interested in seeing how it works, meet us at the Concord Consortium's Booth #2758 in Hall B.

Rainbow, iron, and gray

November 15th, 2011 by Charles Xie

Energy2D is our signature software for simulating invisible energy flow in natural and man-made systems. One of its view shows the temperature distribution calculated by the physics engine. This view renders images similar to what an infrared camera shows. Most IR cameras have a few color palettes for the user to choose. So I think we should provide those options in Energy2D, too.

This blog post shows the three color palettes commonly used in IR imagery that were implemented in Energy2D: rainbow, iron, and gray. I guess the IR folks call the second one "iron" because it looks like the color of an iron bar heated to glow.


A criticism of using colorful heat maps to visualize distributions is the possibility of twisting data and therefore creating illusions--because our perception of color does not go linearly with the linear increase of the RGB values. You can compare these three images and see if that is a problem.

I have blogged a lot about how great an inquiry tool IR imaging represents. The resemblance of Energy2D's temperature patterns to IR images indicates a learning possibility of using simulations to deliver some of the nice features that an IR camera gives--before the prices of IR cameras come down to a couple of hundred dollars.


If you would like to show how they look in real simulations, go to Energy2D's home page and explore from there.